A web application to find patients, build cohorts and visualize health records
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Updated
Mar 17, 2025 - TypeScript
A web application to find patients, build cohorts and visualize health records
R material for LSHTM's Advanced Statistical Methods in Epidemiology (ASME) practical sessions
R material for LSHTM's Statistical Methods in Epidemiology practical sessions
Shiny-Tool for investigation of metabolite-covariate relationships
🫀 Webapp to explore cohorts metadata for the iCARE4CVD project
In order to accelerate progress in cohort studies, we proposed a hierarchical neuroscience knowledge base consisting of projects/organizations, multi-modal databases and toolkits, and take the information object in Frontiers in Neuroscience as a example input. Meanwhile, we developed and open sourced the query tool, PDT_fninf , so that researche…
Clinical-AI Research Framework
'Chai-Cohort' is a repository containing all assignments, notes, and articles related to the Cohort by Hitesh Sir and Piyush Sir.. 😄 It is helpful for beginners to learn and practice
Incidência de correção em tratamento conservador de Camptodacilia: coorte retrospectiva
Effect of socioeconomic status in mortality rates after brain injury: cohort study
R script and Shiny app to perform stratified randomisation
Time-adjusted effect of socioeconomic status in mortality rates after brain injury: cohort study
Sensitivity of mortality rates to the imputation of missing socioeconomic data: cohort study
Generating baseline characteristics table for research studies including clinical trials and large scale cohort studies
SANSCOG-MRI-Pipeline streamlines neuroimaging workflows for the SANSCOG study, offering scripts for preprocessing, data management, extraction, and analysis, ensuring efficient handling of MRI data and reproducible research practices.
Open-source platform for managing longitudinal cohort studies. Features form building, visit scheduling, and secure data management for medical research and clinical trials.
Public content available for LinkR
Consultorias em Estatística Médica e Epidemiologia Clínica. CNPJ:42.154.074/0001-22
Code to accompany "Use of Patient-Reported Symptom Data in Clinical Decision Rules for Predicting Influenza in a Telemedicine Setting" by Billings et al, JABFM 2023
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